1 citations · 2 across the 5 of their papers we have counts for
12 papers
Model-Based Deep Learning for Reconstruction of Joint k-q Under-sampled High Resolution Diffusion MRI
Merry P. Mani, Hemant K. Aggarwal, Sanjay Ghosh +1
We propose a model-based deep learning architecture for the reconstruction of highly accelerated diffusion magnetic resonance imaging (MRI) that enables high resolution imaging. Th…
Label Consistent Transform Learning for Hyperspectral Image Classification
Jyoti Maggu, Hemant K. Aggarwal, Angshul Majumdar
This work proposes a new image analysis tool called Label Consistent Transform Learning (LCTL). Transform learning is a recent unsupervised representation learning approach; we add…
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification
Vanika Singhal, Hemant K. Aggarwal, Snigdha Tariyal +1
This work proposes a new framework for deep learning that has been particularly tailored for hyperspectral image classification. We learn multiple levels of dictionaries in a robus…
Impulse Denoising From Hyper-Spectral Images: A Blind Compressed Sensing Approach
Angshul Majumdar, Naushad Ansari, Hemant Aggarwal +1
In this work we propose a technique to remove sparse impulse noise from hyperspectral images. Our algorithm accounts for the spatial redundancy and spectral correlation of such ima…
Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR)
Aniket Pramanik, Hemant Aggarwal, Mathews Jacob
Structured low-rank (SLR) algorithms, which exploit annihilation relations between the Fourier samples of a signal resulting from different properties, is a powerful image reconstr…
Dynamic MRI using deep manifold self-learning
Abdul Haseeb Ahmed, Hemant Aggarwal, Prashant Nagpal +1
We propose a deep self-learning algorithm to learn the manifold structure of free-breathing and ungated cardiac data and to recover the cardiac CINE MRI from highly undersampled me…